Antoni Morell

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Associate Professor

University of Barcelona

Spain

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About

Dr. Antoni Morell is an Associate Professor at Universitat Autònoma de Barcelona, Spain. His research primarily focuses on artificial intelligence applications, particularly in transfer learning, neural networks, and predicting health outcomes for chronic kidney disease patients. Dr. Morell's recent work includes studies on memristor technology, predictive mortality models, and advanced machine learning techniques for industrial processes.

Recent Grants

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FABRICACION, CARACTERIZACION, SIMULACION, MODELADO Y APLICACIONES DE DISPOSITIVOS DE CONMUTACION RESISTIVA

Open Date: 2018-01-01

Close Date: 2020-12-01

Grant: Close

POSICIONAMIENTO EN ENTORNOS URBANOS Y ADVERSOS MEDIANTE SISTEMAS GNSS Y 5G

Open Date: 2015-01-01

Close Date: 2017-12-01

Grant: Close

APLICACIÓN DE TEORÍA DE JUEGOS A LAS COMUNICACIONES INALÁMBRICAS.

Open Date: 2012-01-01

Close Date: 2012-12-01

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DOLORES REXACHS

Universitat Autònoma de Barcelona (UAB)

SPAIN

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Antoni Morell

Research Interests

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About

Recent Grants

Articles (16)

Predicting transfer learning suitability in ANN-based control of FOPDT industrial processes

Mercado de trabajo y estrategias de valorización

Memristor Crossbar Array Simulation for Deep Learning Applications

#4640 Prediction of Chronic Kidney Disease Progression with Artificial Intelligence: A Challenge Within our Reach

Ternary Neural Networks Based on on/off Memristors: Set-Up and Training

Transfer Learning Improving Predictive Mortality Models for Patients in End-Stage Renal Disease

Multiple imputation using the average code from autoencoders

Machine Learning-Based Prediction of Mortality and Risk Factors in Patients With Chronic Kidney Disease Developed With Data From 10000 Patients Over 11 Years

Transfer Learning Suitability Metric for ANN-based Industrial Controllers

Assessment and Improvement of the Pattern Recognition Performance of Memdiode-Based Cross-Point Arrays with Randomly Distributed Stuck-at-Faults

Transfer Learning in Wastewater Treatment Plant Control Design: From Conventional to Long Short-Term Memory-Based Controllers

Industrial Control under Non-Ideal Measurements: Data-Based Signal Processing as an Alternative to Controller Retuning

Denoising Autoencoders and LSTM-Based Artificial Neural Networks Data Processing for Its Application to Internal Model Control in Industrial Environments—The Wastewater Treatment Plant Control Case

A variational autoencoder solution for road traffic forecasting systems: Missing data imputation, dimension reduction, model selection and anomaly detection

Mortality prediction enhancement in end-stage renal disease: A machine learning approach

Neural network based analysis of random telegraph noise in resistive random access memories

Collaborators (7)

Javier Serrano

Remo Suppi

Enrique Miranda

Jose Lopez Vicario

Jordi Suñe

Jose Ibeas

DOLORES REXACHS

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